| 1. |
- Berger, Christian, 1980
(författare)
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How autonomous driving influences the vehicle's architecture
- 2016
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Ingår i: 2016 Workshop on Automotive Systems/Software Architectures (Wasa). 5-8 April 2016. - : IEEE. - 9781509025718
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Konferensbidrag (refereegranskat)abstract
- Since the 2007 DARPA Urban Challenge, the world's largest experiment with driverless vehicles having to safely interact with each other in a fenced area imitating an urban environment, all important vehicle manufacturers have established research and development around this technology to make driving safer and more comfortable for their customers. The functionality therefore is realized by software outgrowing all individual software units currently present in today's cars to process data volumes, currently in the range of several hundreds megabytes per second from the sensors perceiving a vehicle's surrounding, to derive safe driving decisions. This talk gives an overview of an interdisciplinary research project at Chalmers University of Technology and University of Gothenburg envisioning "CampusShuttle", a self-driving vehicle tackling inner-city driving scenarios. An outline is given for the challenges arising from the embodied technology on the vehicle's sensor architecture, its computing architecture to process the data provided by the on-board and off-board data sources, and its software architecture. Besides these fundamentally necessary aspects, this technology's impact on the test and delivery architecture for the software units as well as the operating deployment architecture is presented and discussed. As the algorithms enabling this technology are predominantly data-driven by the volatile vehicle's driving scenarios, a complete and consistent requirements specification for the building blocks in the software is hardly possible to start with; complementary thereto, recent trends evaluate algorithmic approaches that use growing amounts of data from different driving scenarios in machine learning. In such a highly evolutionary development context, where the software needs to be adapted to better meet requirements that are continuously unveiled during testing and operation, continuous integration of the individual software units comprising a self-driving vehicle system, fast continuous delivery of the resulting executable artifacts to the self-driving vehicle, and their safe and reliable continuous deployment thereon is crucial to prepare experiments, evaluate and learn from the collected data, and to traceably maintain the software environment.
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| 2. |
- Kunze, Sebastian, 1990-, et al.
(författare)
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Generation of Failure Models through Automata Learning
- 2016
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Ingår i: Proceedings. - Los Alamitos : IEEE Computer Society. - 9781509025718 ; , s. 22-25
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Konferensbidrag (refereegranskat)abstract
- In the context of the AUTO-CAAS project that deals with model-based testing techniques applied in the automotive domain, we present the preliminary ideas and results of building generalised failure models for non-conformant software components. These models are a necessary building block for our upcoming efforts to detect and analyse failure causes in automotive software built with AUTOSAR components. Concretely, we discuss how to build these generalised failure models using automata learning techniques applied to a guided model-based testing procedure of a failing component. We illustrate our preliminary findings and experiments on a simple integer queue implemented in the C programming language. © 2016 IEEE.
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| 3. |
- Mohan, Naveen, et al.
(författare)
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Challenges in architecting fully automated driving; With an emphasis on heavy commercial vehicles
- 2016
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Ingår i: Proceedings - 2016 Workshop on Automotive Systems/Software Architectures, WASA 2016. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509025718 ; , s. 2-9
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Konferensbidrag (refereegranskat)abstract
- Fully automated vehicles will require new functionalities for perception, navigation and decision making - an Autonomous Driving Intelligence (ADI). We consider architectural cases for such functionalities and investigate how they integrate with legacy platforms. The cases range from a robot replacing the driver - with entire reuse of existing vehicle platforms, to a clean-slate design. Focusing on Heavy Commercial Vehicles (HCVs), we assess these cases from the perspectives of business, safety, dependability, verification, and realization. The original contributions of this paper are the classification of the architectural cases themselves and the analysis that follows. The analysis reveals that although full reuse of vehicle platforms is appealing, it will require explicitly dealing with the accidental complexity of the legacy platforms, including adding corresponding diagnostics and error handling to the ADI. The current fail-safe design of the platform will also tend to limit availability. Allowing changes to the platforms, will enable more optimized designs and fault-operational behaviour, but will require initial higher development cost and specific emphasis on partitioning and control to limit the influences of safety requirements. For all cases, the design and verification of the ADI will pose a grand challenge and relate to the evolution of the regulatory framework including safety standards.
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| 4. |
- Pelliccione, Patrizio, 1975, et al.
(författare)
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A proposal for an Automotive Architecture Framework for Volvo Cars
- 2016
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Ingår i: Workshop on Automotive Systems/Software Architectures (WASA), Venice, Italy, April 05-08, 2016. - 9781509025718 ; , s. 18-21
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Konferensbidrag (refereegranskat)abstract
- © 2016 IEEE. During the past twenty years vehicles have become more and more robot like, interpreting and exploiting input from various sensors to make decisions and finally commit actions that were previously made by humans. Such features will require continuous evolution and updates to ensure safety, security, and suitability for supporting drivers in an ever changing world. Modern vehicles can have over 100 Electronic Control Units (ECUs), which are small computers, together executing gigabytes of software. ECUs are connected to each other through severalnetworks within the car, and in some cases also to the outside world. This need for addressing ever increasing complexity as well as for offering flexibility, support of continuous evolution, and very late changes in user visible features introduces new challenges for developing and maintaining a suitable electronic architecture. In this paper we report the current investigation of the Volvo Cars to create an architecture framework tailored to the needs of future vehicles.
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